Octree Based Representation and Volume Rendering of Three-Dimensional Medical Data Sets

In many clinical applications, interactive exploration of three dimension medical data sets is required, but the huge amount of computational time and storage space needed for rendering do not allow the visualization of large medical data sets by now. In this paper we present a new algorithm for rendering large medical data sets on standard PC. The key technique is a new representation method of large medical dataset based on an efficient octree data structure. First, the input data is converted into a compressed hierarchical octree representation. Then, a template-based raycasting scheme using shear-warp factorization for expediting parallel viewing of volume datasets is employed. The algorithm exploits the uniform shape, orientation and size of the "nonempty" octree blocks by building templates for ray/block intersections in the case of raycasting. Experiment results display that high quality human body interior images of a large dataset can be generated by the proposed approach on a standard PC platform fast.